Many animal management events experienced by livestock throughout the animal's lifetime can influence its overall welfare, performance (e.g. the quality of food it produces), and the cost of agricultural resources required. For instance, exposure to handling and transport, co-mingling, auction and time off feed can cause stress in animals, impeding their immune system and increasing the incidence of disease. Left unmanaged, such events can have a considerable economic impact on the agricultural industry. The use of agricultural resources for the production of animal products is increasingly being scrutinised as human populations expand, increasing the need to mitigate carbon footprints and greenhouse gas emissions. Monitoring and controlling the impact animal management events can lead to improved animal welfare and quality, and to overall environmental benefits such as reduced carbon footprint and greenhouse gas emissions.
Effective animal management can depend upon the ability to rapidly and non-invasively determine when animals are in steady or non-steady states (e.g. disease state, reproductive states, or growth phases). Monitoring these biological states is important to the agricultural industry, as well as to zoo and wildlife biology settings because they can influence a plethora of biometric measurements and characteristics, such as an animal's metabolic efficiency.
Metabolic efficiency has become an important attribute in animal agriculture as competition for limited resources increases. Variation in inherent or normal growth efficiency among animals within a species can be large, at least in part due to genetic variation in feed conversion efficiency. Feed accounts for a large proportion of input costs required to raise livestock in all phases of production, so it is vital that producers get the most value for their feed. However, measuring an animal's metabolic efficiency has always been a challenge as many factors, including genetics, can dictate how feed affects the metabolic efficiencies of livestock.
Feed or growth efficiency is the measure of energy or feed resources required for a given gain in an identifiable animal product such as meat, milk or wool. Animals with poor feed efficiency not only grow less efficiently, but also produce more carbon dioxide and methane than higher feed efficiency animals, making it desirable for producers to be able to sort and select animals based on their feed efficiency. For example, in some animals, it is estimated that 70% of the food energy requirements used by an animal are actually spent on maintenance of the animal, not on growth or gain in an identifiable animal product such as meat, milk or wool. Further, animals with poor feed efficiency tend to produce more methane than the average animal because less of the ingested biomass is converted to energy, instead being converted to waste by-products such as methane. As such, the measurement of animal metabolic efficiency is a prime directive in animal agriculture, as the selection of only the most efficient animals by producers improves efficiency in the use feed resources.
Several techniques exist for classifying live animals into feed efficiency categories without predicting or measuring actual feed efficiency. Ultrasound can be used to score animals based on their body conditioning and frame size, however this approach merely selects larger body size, which is not a consistent indicator of feed efficiency. The “Kleiber ratio,” which evaluates an animal's metabolic rate based on its mass, can be used but again only provides for the selection larger body size. Known methods fail to account for variation in growth efficiency based on the overall health or the genetics of the animal.
One of the more accurate methods for monitoring feed efficiency is to use indirect calorimetry which measures exactly the amount of oxygen and energy used by an animal for a given increase in gain of a specific tissue while noting that the metabolism will also give off heat. This method requires the use of expensive and complex indirect calorimetry equipment, the training of animals and the necessity to conduct trials at a physiological steady state.
A more recent approach to monitoring feed or growth efficiency is to monitor the residual feed intake (RFI) value, which partitions feed intake into that used for production and a residual portion reflecting efficiency. Fundamentally, this process compares the measured feed-to-gain against a known estimate for feed-to-gain, based on scientifically accepted formulas. While reasonably accurate, the RFI method requires a lengthy monitoring period of at least seventy days making it both expensive and impractical.
U.S. patent application Ser. No. 10/558,854 (Publication No. US2007/0093965 A1) filed by Harry Harrison et al. (“Harrison”) teaches the use of infrared thermography (IRT) to determine or predict growth efficiency in animals. Infrared thermography is a known method of detecting the dissipation of heat from animals and operates on the principle that infrared radiation can be utilized to observe radiated heat loss and to provide an early indicator of fever because up to 60% of the heat loss from an animal occurs in infrared ranges. While IRT can be an effective in non-invasive identification of transport and other environmental stressors, the Harrison method requires that sufficient animals be sampled to over long periods of time (several weeks or months) to provide enough data to predict animal growth. As such, the method is not suitable for rapidly determining the metabolic efficiency of one animal at a time.
Further, the Harrison method requires that the animals be in a steady-state condition, meaning that the animal's endocrine, physiological and metabolic value are all within a normal range and the animal is not stressed. It is well known, however, that animals often do not display overt signs of illness or a non-steady state (that would be detectable by a caregiver) until later in the progression of the disease. As such, despite the Harrison method expressly attempting to exclude animals in a non-steady state, it is entirely possible that the collected values from many animals could be skewed as a result of inadvertently including animals having an abnormal thermal expression.
There is a need for a non-invasive means for identifying metabolic efficiency in livestock without requiring the animal to be in a steady-state condition, enabling producers to rapidly determine each animal's overall health and performance, and to predict its response to various animal management events (e.g. disease, stress, growth, reproduction). The method could provide for the ranking, selection, breeding and/or culling of animals based upon their efficiency, adding value to the herd and decreasing production and environmental costs.